DOCSLIB.ORG

Dominant Algae of Otsego Lake, Cooperstown, NY

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Dominant algae of Otsego Lake, Cooperstown, NY Claire Garfield 1 INTRODUCTION The diversity and frequency of algal species are important factors in determining limnological conditions because algae serve as a biological indicator of ecological stability and water quality (Bellinger and Sigee 2010). While Otsego Lake is considered a meso-oligotrophic lake, data relating to the composition of the algal standing crop in Otsego Lake would be advantageous in further determining the state of the lake (Godfrey 1977). Certain species of algae are indicative of water quality. Some groups of diatoms (Bacillariophyceae) and golden-brown algae (Chrysophyceae) grow only in relatively unpolluted water whereas cyanobacteria are more tolerant of pollution (Baker 2012). Therefore the relative abundance of any given group of algae can reveal much about the health of a lake (Bellinger and Sigee 2010).The importance of knowing the taxonomic composition of algae in Otsego Lake is augmented by the fact that many genera of cyanobacteria, often referred to as blue-green algae, produce toxins as secondary metabolites involved in storing nitrogen (Baker 2012). Many of these toxins are neuro- or hepatotoxins. Beta-Methylamino-L-alanine (BMAA), a toxin capable of being produced by multiple species of cyanobacteria has been linked to amyotrophic lateral sclerosis (ALS) or Lou Gehrig’s disease (Cox et al. 2003). The purpose of this study was to identify and determine the relative dominance of major planktonic algal taxa in Otsego Lake using both conventional microscopy as well as a Fluid Imaging Technnologies FlowCam®, a digital particle analyzer (FlowCam 2011). METHODS Samples were taken bi-weekly at the deepest point (50m) in Otsego Lake, TR4-C (Figure 1). Two garden hoses attached to a weighted line were lowered to a depth of 20 meters and retrieved from the bottom, yielding a single composite sample. The contents of the hoses were emptied out into a one gallon Nalgene® bottle made of high density polypropylene. 1 F.H.V. Mecklenburg Conservation Fellow, summer 2015. Present affiliation: Oneonta High School. Funding provided by the Otsego County Conservation Association. Figure 1. Map of Otsego Lake showing the sampling site for algae. Samples were preserved with Lugol’s iodine solution, which also later helped the algal cells settle out of suspension in Utermöhl chambers. The samples were stored in the cold room until further processing to prevent degradation of the algae. Samples were analyzed in two ways: one with manual counts with an inverted microscope and another with FlowCam® . Samples viewed with a microscope were inverted several times and placed in a 10-mL KC Denmark A/S Utermöhl chamber and viewed with the Zeiss Axiovert 25 inverted microscope. Cell counts were taken and recorded for the entire bottom area of the chamber. Samples viewed with FlowCam® were analyzed as follows. Approximately 3mL of undiluted sample was processed through the flow cell. FlowCam® then took images of the first 1000 particles. Those pictures were then identified and sorted into various libraries to be counted. FlowCam® was much more proficient at identifying cells on new samples; however, on older samples, the microscope proved a better method. A function and asset of using FlowCam® is that it can analyze data quickly and compensate for error involved in taking a subsample. However, using FlowCam® did pose some problems. The most common pictures taken were either of detritus or non-algal particles, and the poor quality of many pictures prevented them from being used. Algae were counted by cell as opposed to colonies; however, Microcystis and Anabaena were counted by colony and filament, respectively. RESULTS AND DISCUSSION Table 1 summarizes the particle counts acquired using the microscope from samples collected from 21 April 2014 to 12 August 2015 (cell counts for most, colony counts for Microcystis and Anabaena). Similarly, Table 2 summarizes particle counts acquired using the FlowCam® on samples collected from 19 May to 12 August 2015. Here, cells are not differentiated from particles (i.e., cells). Figure 2 and 3 summarize the microscope counts and FlowCam® counts, respectively. Similarly, Figures 4 and 5 summarize the total counts using the microscope and FlowCam® during the summer of 2015 (19 May to 12 August). 4/21/14 5/7/14 6/18/14 6/21/14 7/2/14 9/7/14 9/13/14 10/27/14 11/10/14 5/19/15 6/3/15 7/2/15 8/12/15 8/27/15 9/16/15 10/6/15 10/21/15 TOTAL MICROCYSTIS 0 0 0 0 1.3 0 0 0 1.6 0.5 0.1 0 0.2 0.4 0.3 0.6 0.1 5.1 ANABAENA 0 0.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.1 CYCLOTELLA 0.1 0.3 0.2 0 0.4 0 0 0 0 0.1 0 0.5 1.2 11.5 0 0.2 0.1 14.6 ASTERIONELLA 7.2 5 0.2 2.4 1.4 0 0 2.6 0 0 0 0.8 0 0 0 0 0 19.6 FRAGILARIA 0.3 0 0 0 0 0 0 2.5 5.5 0.4 3.2 0.6 26.7 8 0 2.1 0.1 49.4 PINNATE DIATOMS 0.8 4.3 0 1.5 0.1 0 0.6 0.6 0 0.4 0.2 0.2 0.2 0.3 0 0.1 0.8 10.1 DINOBRYON 0.1 0 5.3 0.2 1.4 0.8 0.7 1 0 0 3.7 1.6 0.6 2 1.8 1.2 7.6 28 PERIDINIUM 0 0 0 0 0.1 0 0 0 0 0 0 0 0 0 0 0.1 0 0.2 CERATIUM 0 0 0 0 0.1 0 0 0 0 0 0 0 0.1 0 0 0 0 0.2 EUGLENA 0 0 0 0 0 0 0.1 0 0 0 0.1 0 0 0 0 0 0 0.2 MOUGEOTIA 15.8 29.3 2.9 13.9 3.2 6.8 0 6.5 2.8 1.1 4 6.6 8.6 5.3 1.3 2.4 15.8 126.3 GLOEOCYSTIS 0 0 0.2 0 8.2 3.6 0 7.1 2.2 32.3 1.5 422.3 445.6 105.7 77.6 4 3.2 1113.5 PEDIASTRUM 0 0 0 0 0 0 0 6.4 0 0 0 0 3 0 0 3 0 12.4 Table 1. The total number of cells (#/ml) (except for Microcystis and Anabaena, which were counted as colonies) counted with the microscope, by genus and date. 5/19/15 6/3/15 6/7/15 7/2/15 7/14/15 8/12/15 TOTAL MICROCYSTIS 2 2 2 0 6 0 12 ANABAENA 0 0 0 1 0 6 7 CYCLOTELLA 0 0 0 0 0 0 0 ASTERIONELLA 0 0 0 0 0 0 0 FRAGILARIA 0 0 0 0 0 0 0 PINNATE DIATOMS 0 0 0 0 0 1 1 DINOBRYON 0 0 14 1 0 0 15 PERIDINIUM 0 0 0 0 0 0 0 CERATIUM 0 0 0 0 0 0 0 EUGLENA 2 0 0 0 0 0 2 MOUGEOTIA 0 0 0 0 0 0 0 GLOEOCYSTIS 20 0 30 97 79 34 260 Table 2. The number of particles counted with FlowCam® for 2015 (#/ml) by genus and date. Microscope 4/21/14 500 5/7/14 450 6/18/14 400 6/21/14 350 300 7/2/14 250 9/7/14 200 10/27/14 150 AMOUNT OF CELLS 11/10/14 100 50 5/19/15 0 6/3/15 7/2/15 8/12/15 GENERA Figure 2. The total number of cells (except for Microcystis and Anabaena, which were counted as colonies) counted with the microscope by genus and date. FLOWCAM® 120 100 5/19/15 6/3/15 80 6/7/15 60 7/2/15 40 7/14/15 AMOUNT OF CELLS 8/12/15 20 0 GENERA Figure 3. The number of particles counted with FlowCam® for 2015 by genus and date. Microscope totals 1200 1000 800 600 400 AMOUNT OF CELLS 200 0 GENERA Figure 4. The total amount of cells counted manually by genus and date between 21 April and 27 August 2015. FLOWCAM® totals 300 250 200 150 100 AMOUNT OF CELLS 50 0 GENERA Figure 5. Represents total amount of particles counted by genus with FlowCam® between 21 April and 27 August 2015. The most ubiquitous group of algae in Otsego Lake was Gloeocystis (Figure 6). Gloeocystis is a member of the subkingdom Chlorophyta. The value of Gloeocystis as a biological indicator is limited; however, large quantities, much larger than those of Otsego Lake, can cause an unpleasant smell (Guiry and Guiry 2015). Figure 6. Gloeocystis. Scale bar = 12.5 µm. The second most abundant species of algae in Otsego Lake was Mougeotia (Figure 7), a member of charophyceae. Mougeotia is spread throughout the world and is not considered a nuisance (Guiry and Guiry 2015). Figure 7. Mougeotia. Scale bar = 12.5 µm. Dinobryon, a genus of Chrysophyceae (golden-browns), was also found frequently (Figure 8). Dinobryon is dependent upon oligotrophic conditions making it an excellent biological indicator. Thus the frequency of Dinobryon suggested a more oligotrophic lake (Baker 2012). Figure 8. Dinobryon. Scale bar = 12.5 µm. The most diverse group in Otsego Lake and all fresh water is Bacillariophyceae, commonly known as diatoms.
Recommended publications
  • Red Algae (Bangia Atropurpurea) Ecological Risk Screening Summary

    Red Algae (Bangia Atropurpurea) Ecological Risk Screening Summary

    Red Algae (Bangia atropurpurea) Ecological Risk Screening Summary U.S. Fish & Wildlife Service, February 2014 Revised, March 2016, September 2017, October 2017 Web Version, 6/25/2018 1 Native Range and Status in the United States Native Range From NOAA and USGS (2016): “Bangia atropurpurea has a widespread amphi-Atlantic range, which includes the Atlantic coast of North America […]” Status in the United States From Mills et al. (1991): “This filamentous red alga native to the Atlantic Coast was observed in Lake Erie in 1964 (Lin and Blum 1977). After this sighting, records for Lake Ontario (Damann 1979), Lake Michigan (Weik 1977), Lake Simcoe (Jackson 1985) and Lake Huron (Sheath 1987) were reported. It has become a major species of the littoral flora of these lakes, generally occupying the littoral zone with Cladophora and Ulothrix (Blum 1982). Earliest records of this algae in the basin, however, go back to the 1940s when Smith and Moyle (1944) found the alga in Lake Superior tributaries. Matthews (1932) found the alga in Quaker Run in the Allegheny drainage basin. Smith and 1 Moyle’s records must have not resulted in spreading populations since the alga was not known in Lake Superior as of 1987. Kishler and Taft (1970) were the most recent workers to refer to the records of Smith and Moyle (1944) and Matthews (1932).” From NOAA and USGS (2016): “Established where recorded except in Lake Superior. The distribution in Lake Simcoe is limited (Jackson 1985).” From Kipp et al. (2017): “Bangia atropurpurea was first recorded from Lake Erie in 1964. During the 1960s–1980s, it was recorded from Lake Huron, Lake Michigan, Lake Ontario, and Lake Simcoe (part of the Lake Ontario drainage).
  • Seasonal and Interannual Changes in Ciliate and Dinoflagellate

    Seasonal and Interannual Changes in Ciliate and Dinoflagellate

    ORIGINAL RESEARCH published: 07 February 2017 doi: 10.3389/fmars.2017.00016 Seasonal and Interannual Changes in Ciliate and Dinoflagellate Species Assemblages in the Arctic Ocean (Amundsen Gulf, Beaufort Sea, Canada) Edited by: Deo F. L. Onda 1, 2, 3, Emmanuelle Medrinal 1, 3, André M. Comeau 1, 3 †, Mary Thaler 1, 2, 3, George S. Bullerjahn, Marcel Babin 1, 2 and Connie Lovejoy 1, 2, 3* Bowling Green State University, USA Reviewed by: 1 Département de Biologie and Québec-Océan, Université Laval, Quebec, QC, Canada, 2 Takuvik, Joint International Rebecca Gast, Laboratory, UMI 3376, Centre National de la Recherche Scientifique (CNRS, France) and Université Laval, Québec, QC, Woods Hole Oceanographic Canada, 3 Institut de Biologie Intégrative et des Systèmes, Université Laval, Quebec, QC, Canada Institution, USA Alison Clare Cleary, Independent Researcher, San Recent studies have focused on how climate change could drive changes in Francisco, United States phytoplankton communities in the Arctic. In contrast, ciliates and dinoflagellates that can *Correspondence: contribute substantially to the mortality of phytoplankton have received less attention. Connie Lovejoy Some dinoflagellate and ciliate species can also contribute to net photosynthesis, [email protected] which suggests that species composition could reflect food web complexity. To identify †Present Address: André M. Comeau, potential seasonal and annual species occurrence patterns and to link species with Centre for Comparative Genomics and environmental conditions, we first examined the seasonal pattern of microzooplankton Evolutionary Bioinformatics-Integrated Microbiome Resource, Department of and then performed an in-depth analysis of interannual species variability. We used Pharmacology, Dalhousie University, high-throughput amplicon sequencing to identify ciliates and dinoflagellates to the lowest Canada taxonomic level using a curated Arctic 18S rRNA gene database.
  • Lateral Gene Transfer of Anion-Conducting Channelrhodopsins Between Green Algae and Giant Viruses

    Lateral Gene Transfer of Anion-Conducting Channelrhodopsins Between Green Algae and Giant Viruses

    bioRxiv preprint doi: https://doi.org/10.1101/2020.04.15.042127; this version posted April 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 5 Lateral gene transfer of anion-conducting channelrhodopsins between green algae and giant viruses Andrey Rozenberg 1,5, Johannes Oppermann 2,5, Jonas Wietek 2,3, Rodrigo Gaston Fernandez Lahore 2, Ruth-Anne Sandaa 4, Gunnar Bratbak 4, Peter Hegemann 2,6, and Oded 10 Béjà 1,6 1Faculty of Biology, Technion - Israel Institute of Technology, Haifa 32000, Israel. 2Institute for Biology, Experimental Biophysics, Humboldt-Universität zu Berlin, Invalidenstraße 42, Berlin 10115, Germany. 3Present address: Department of Neurobiology, Weizmann 15 Institute of Science, Rehovot 7610001, Israel. 4Department of Biological Sciences, University of Bergen, N-5020 Bergen, Norway. 5These authors contributed equally: Andrey Rozenberg, Johannes Oppermann. 6These authors jointly supervised this work: Peter Hegemann, Oded Béjà. e-mail: [email protected] ; [email protected] 20 ABSTRACT Channelrhodopsins (ChRs) are algal light-gated ion channels widely used as optogenetic tools for manipulating neuronal activity 1,2. Four ChR families are currently known. Green algal 3–5 and cryptophyte 6 cation-conducting ChRs (CCRs), cryptophyte anion-conducting ChRs (ACRs) 7, and the MerMAID ChRs 8. Here we 25 report the discovery of a new family of phylogenetically distinct ChRs encoded by marine giant viruses and acquired from their unicellular green algal prasinophyte hosts.
  • Phytoref: a Reference Database of the Plastidial 16S Rrna Gene of Photosynthetic Eukaryotes with Curated Taxonomy

    Phytoref: a Reference Database of the Plastidial 16S Rrna Gene of Photosynthetic Eukaryotes with Curated Taxonomy

    Molecular Ecology Resources (2015) 15, 1435–1445 doi: 10.1111/1755-0998.12401 PhytoREF: a reference database of the plastidial 16S rRNA gene of photosynthetic eukaryotes with curated taxonomy JOHAN DECELLE,*† SARAH ROMAC,*† ROWENA F. STERN,‡ EL MAHDI BENDIF,§ ADRIANA ZINGONE,¶ STEPHANE AUDIC,*† MICHAEL D. GUIRY,** LAURE GUILLOU,*† DESIRE TESSIER,††‡‡ FLORENCE LE GALL,*† PRISCILLIA GOURVIL,*† ADRIANA L. DOS SANTOS,*† IAN PROBERT,*† DANIEL VAULOT,*† COLOMBAN DE VARGAS*† and RICHARD CHRISTEN††‡‡ *UMR 7144 - Sorbonne Universites, UPMC Univ Paris 06, Station Biologique de Roscoff, Roscoff 29680, France, †CNRS, UMR 7144, Station Biologique de Roscoff, Roscoff 29680, France, ‡Sir Alister Hardy Foundation for Ocean Science, The Laboratory, Citadel Hill, Plymouth PL1 2PB, UK, §Marine Biological Association, The Laboratory, Citadel Hill, Plymouth PL1 2PB, UK, ¶Stazione Zoologica Anton Dohrn, Villa Comunale, Naples 80121, Italy, **The AlgaeBase Foundation, c/o Ryan Institute, National University of Ireland, University Road, Galway Ireland, ††CNRS, UMR 7138, Systematique Adaptation Evolution, Parc Valrose, BP71, Nice F06108, France, ‡‡Universite de Nice-Sophia Antipolis, UMR 7138, Systematique Adaptation Evolution, Parc Valrose, BP71, Nice F06108, France Abstract Photosynthetic eukaryotes have a critical role as the main producers in most ecosystems of the biosphere. The ongo- ing environmental metabarcoding revolution opens the perspective for holistic ecosystems biological studies of these organisms, in particular the unicellular microalgae that
  • The Origin and Evolution of Model Organisms

    The Origin and Evolution of Model Organisms

    REVIEWS THE ORIGIN AND EVOLUTION OF MODEL ORGANISMS S. Blair Hedges The phylogeny and timescale of life are becoming better understood as the analysis of genomic data from model organisms continues to grow. As a result, discoveries are being made about the early history of life and the origin and development of complex multicellular life. This emerging comparative framework and the emphasis on historical patterns is helping to bridge barriers among organism-based research communities. Model organisms represent only a small fraction of the these species are receiving an unusually large amount of biodiversity that exists on Earth, although the research attention from the research community and fall under that has resulted from their study forms the core of bio- the broad definition of “model organism”. logical knowledge. Historically, research communities Knowledge of the relationships and times of origin of — often in isolation from one another — have focused these species can have a profound effect on diverse areas on these model organisms to gain an insight into the of research2. For example, identifying the closest relatives general principles that underlie various disciplines, such of a disease vector will help to decipher unique traits — as genetics, development and evolution. This has such as single-nucleotide polymorphisms — that might changed in recent years with the availability of complete contribute to a disease phenotype. Similarly, knowing genome sequences from many model organisms, which that our closest relative is the chimpanzee is crucial for has greatly facilitated comparisons between the different identifying genetic changes in coding and regulatory species and increased interactions among organism- genomic regions that are unique to humans, and are based research communities.
  • Proposal for Practical Multi-Kingdom Classification of Eukaryotes Based on Monophyly 2 and Comparable Divergence Time Criteria

    Proposal for Practical Multi-Kingdom Classification of Eukaryotes Based on Monophyly 2 and Comparable Divergence Time Criteria

    bioRxiv preprint doi: https://doi.org/10.1101/240929; this version posted December 29, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Proposal for practical multi-kingdom classification of eukaryotes based on monophyly 2 and comparable divergence time criteria 3 Leho Tedersoo 4 Natural History Museum, University of Tartu, 14a Ravila, 50411 Tartu, Estonia 5 Contact: email: [email protected], tel: +372 56654986, twitter: @tedersoo 6 7 Key words: Taxonomy, Eukaryotes, subdomain, phylum, phylogenetic classification, 8 monophyletic groups, divergence time 9 Summary 10 Much of the ecological, taxonomic and biodiversity research relies on understanding of 11 phylogenetic relationships among organisms. There are multiple available classification 12 systems that all suffer from differences in naming, incompleteness, presence of multiple non- 13 monophyletic entities and poor correspondence of divergence times. These issues render 14 taxonomic comparisons across the main groups of eukaryotes and all life in general difficult 15 at best. By using the monophyly criterion, roughly comparable time of divergence and 16 information from multiple phylogenetic reconstructions, I propose an alternative 17 classification system for the domain Eukarya to improve hierarchical taxonomical 18 comparability for animals, plants, fungi and multiple protist groups. Following this rationale, 19 I propose 32 kingdoms of eukaryotes that are treated in 10 subdomains. These kingdoms are 20 further separated into 43, 115, 140 and 353 taxa at the level of subkingdom, phylum, 21 subphylum and class, respectively (http://dx.doi.org/10.15156/BIO/587483).
  • Freshwater Algae Associated with High Elevation Bogs in the Hawaiian Islands 1

    Freshwater Algae Associated with High Elevation Bogs in the Hawaiian Islands 1

    Records of the Hawaii Biological Survey for 2012. Edited by Neal L. Evenhuis & Lucius G. Eldredge. Bishop Museum Occasional Papers 114: 21 –31 (2013) Freshwater algae associated with high elevation bogs in the Hawaiian Islands 1 AliSoN R. S HeRWood 2, AMY l. C ARlile 3 Botany Department, 3190 Maile Way, University of Hawai‘i, Honolulu, Hawai‘i 96822 USA; email: [email protected] JoHN d. H All Department of Botany, Academy of Natural Sciences, 1900 Benjamin Franklin Parkway, Philadelphia, PA 19103 USA; email: [email protected] JeSSiCA M. N eUMANN Botany Department, 3190 Maile Way, University of Hawai‘i, Honolulu, Hawai‘i 96822 USA; email: [email protected] As part of the Hawaiian Freshwater Algae Biodiversity Survey (2009 –2012) we have been documenting algae (with a focus on macroalgae) associated with numerous habitats, including high elevation bogs on the main Hawaiian islands. Bogs represent a very dif - ferent environment from streams, where most of our collections originated, in that they have much lower (or absent) water flow, lower temperatures due to high elevation, and usually acidic pH conditions. This paper provides an updated taxonomic checklist for high elevation bog-associated algae in Hawai‘i and compares our identifications to historical literature records. Hawaiian bog ecosystems are characterized as small, isolated and permanently wet areas, which tend to be scarce (only 1 –2 present on each large island), consisting of hum - mocks of native sedges and dwarf individuals of native plant species (Ziegler 2002). in general, bogs represent acidic, dystrophic environments that have a very characteristic lit - toral flora (Wetzel 2001).
  • Macroalgae (Seaweeds)

    Macroalgae (Seaweeds)

    Published July 2008 Environmental Status: Macroalgae (Seaweeds) © Commonwealth of Australia 2008 ISBN 1 876945 34 6 Published July 2008 by the Great Barrier Reef Marine Park Authority This work is copyright. Apart from any use as permitted under the Copyright Act 1968, no part may be reproduced by any process without prior written permission from the Great Barrier Reef Marine Park Authority. Requests and inquiries concerning reproduction and rights should be addressed to the Director, Science, Technology and Information Group, Great Barrier Reef Marine Park Authority, PO Box 1379, Townsville, QLD 4810. The opinions expressed in this document are not necessarily those of the Great Barrier Reef Marine Park Authority. Accuracy in calculations, figures, tables, names, quotations, references etc. is the complete responsibility of the authors. National Library of Australia Cataloguing-in-Publication data: Bibliography. ISBN 1 876945 34 6 1. Conservation of natural resources – Queensland – Great Barrier Reef. 2. Marine parks and reserves – Queensland – Great Barrier Reef. 3. Environmental management – Queensland – Great Barrier Reef. 4. Great Barrier Reef (Qld). I. Great Barrier Reef Marine Park Authority 551.42409943 Chapter name: Macroalgae (Seaweeds) Section: Environmental Status Last updated: July 2008 Primary Author: Guillermo Diaz-Pulido and Laurence J. McCook This webpage should be referenced as: Diaz-Pulido, G. and McCook, L. July 2008, ‘Macroalgae (Seaweeds)’ in Chin. A, (ed) The State of the Great Barrier Reef On-line, Great Barrier Reef Marine Park Authority, Townsville. Viewed on (enter date viewed), http://www.gbrmpa.gov.au/corp_site/info_services/publications/sotr/downloads/SORR_Macr oalgae.pdf State of the Reef Report Environmental Status of the Great Barrier Reef: Macroalgae (Seaweeds) Report to the Great Barrier Reef Marine Park Authority by Guillermo Diaz-Pulido (1,2,5) and Laurence J.
  • Marine Macroalgae and Associated Flowering Plants from the Keret Archipelago, White Sea, Russiaa

    Marine Macroalgae and Associated Flowering Plants from the Keret Archipelago, White Sea, Russiaa

    Research Article Algae 2013, 28(3): 267-280 http://dx.doi.org/10.4490/algae.2013.28.3.267 Open Access Marine macroalgae and associated flowering plants from the Keret Archipelago, White Sea, Russiaa David J. Garbary1,* and Elena R. Tarakhovskaya2 1Department of Biology, St. Francis Xavier University, Antigonish, NS B2G 2W5, Canada 2Department of Plant Physiology and Biochemistry, St. Petersburg State University, St. Petersburg 199034, Russia The marine algal flora of the Keret Archipelago (66° N, 33° E) in the White Sea, Russia was investigated during 2008. Over 250 algal records from more than 15 islands and several sites on the adjoining mainland produced a total of 62 algal species. This raised the total from 56 to 88 species of Chlorophyta (23 species), Phaeophyceae (31 species), Rhodophyta (33 species), and Tribophyceae (1 species) of which seven were new records or verifications of ambiguous records for the White Sea and 11 species are new for the Keret Archipelago. The new or confirmed records included species ofBlidin - gia, Eugomontia, Prasiola, Rosenvingiella, and Ulothrix (Chlorophyta), Acrochaetium, Colaconema (Rhodophyta), and Vaucheria (Tribophyceae). Five species of flowering plants Aster( , Plantago, Triglochin, and Zostera) were associated with the macrophytic algal vegetation of the region. Five fucoid algae in Pelvetia, Fucus, and Ascophyllum provide a picture of a temperate flora. Regardless, the overall species richness is consistent with an arctic nature to the flora. This discrepancy is attributed to the ‘filter’ provided by the Barents Sea of the Arctic Ocean for post-glacial colonization of the White Sea. Key Words: biogeography; Chlorophyta; Keret Archipelago; Prasiolales; Russia; White Sea INTRODUCTION The White Sea is a cold temperate extension of the po- a range of estuarine habitats from near freshwater sites lar Barents Sea and Arctic Ocean.
  • Chapter 1 Introduction

    Chapter 1 Introduction

    Chapter 1 Introduction The idea for this guide began in 2006 when the Institute for Watershed Studies (www.wwu.edu/iws) expanded its Northwest Lakes monitoring project to collect water quality samples from more than 70 local lakes. Plankton samples collected from these lakes and other sites formed the basis for the Institute’s online digital image library of freshwater algae and provided the material I needed to develop this guide. The first version of this guide was finished in the spring of 2009 and used as a class reference for ESCI 428, Freshwater Algal Bioindicators. After much additional sampling and taxonomic effort, the guide expanded to the point where it was not feasible to print as a single volume. As a result, the current version has been separated into multiple volumes as described in Table 1.1 (page6). Although the emphasize is on freshwater lakes, samples collected in streams, seeps, waterfalls, and other lotic systems are included, with comments on whether the taxa1 are likely to be found in plankton samples. All identifications represent my best effort to provide accurate classifications using major keys (John, et al., 2011; Komarek,´ 2013; Komarek´ & Anagnostidis, 1998; 2005; Prescott, 1962; Wehr, et al., 2015); and other taxonomic sources listed in Section6 (page 481). Uncertain identifications were flagged using a “?” following the species name.2 Unknown taxa that could be separated using 1The word “taxa” (singular “taxon”) is used to distinguish unique groups of organisms. 2Taxonomists often use “cf” (Latin: conferre or conformis) or “aff” (Latin: affinis) to indicate taxonomic uncertainty, but these terms have distinctions that are beyond the scope of this guide.
  • Genera of the World: an Overview and Estimates Based on the March 2020 Release of the Interim Register of Marine and Nonmarine Genera (IRMNG)

    Genera of the World: an Overview and Estimates Based on the March 2020 Release of the Interim Register of Marine and Nonmarine Genera (IRMNG)

    Megataxa 001 (2): 123–140 ISSN 2703-3082 (print edition) https://www.mapress.com/j/mt/ MEGATAXA Copyright © 2020 Magnolia Press Article ISSN 2703-3090 (online edition) https://doi.org/10.11646/megataxa.1.2.3 http://zoobank.org/urn:lsid:zoobank.org:pub:F4A52C97-BAD0-4FD5-839F-1A61EA40A7A3 All genera of the world: an overview and estimates based on the March 2020 release of the Interim Register of Marine and Nonmarine Genera (IRMNG) TONY REES 1, LEEN VANDEPITTE 2, 3, BART VANHOORNE 2, 4 & WIM DECOCK 2, 5 1 Private address, New South Wales, Australia. �[email protected]; http://orcid.org/0000-0003-1887-5211 2 Flanders Marine Institute/Vlaams Instituut Voor De Zee (VLIZ), Wandelaarkaai 7, 8400 Ostend, Belgium. 3 �[email protected]; http://orcid.org/0000-0002-8160-7941 4 �[email protected]; https://orcid.org/0000-0002-6642-4725 5 �[email protected]; https://orcid.org/0000-0002-2168-9471 Abstract Introduction We give estimated counts of known accepted genera of the The concept of a series of papers addressing portions of world (297,930±65,840, of which approximately 21% are the question of “all genera of the world” is a valuable one, fossil), of a total 492,620 genus names presently held for which can benefit from as much preliminary scoping as “all life”, based on the March 2020 release of the Interim may be currently available. To date, synoptic surveys of Register of Marine and Nonmarine Genera (IRMNG). A fur- biodiversity have been attempted mainly at the level of ther c.
  • The Evolution of Multicellular Complexity: the Role of Relatedness And

    The Evolution of Multicellular Complexity: the Role of Relatedness And

    bioRxiv preprint doi: https://doi.org/10.1101/836940; this version posted November 9, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 The evolution of multicellular complexity: the role of relatedness and 2 environmental constraints 3 4 Fisher, RM1, Shik, JZ1,2 & Boomsma, JJ1 5 1Section for Ecology and Evolution, Department of Biology, University of Copenhagen, 6 Denmark 7 2Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Ancon, Republic 8 of Panama 9 10 Keywords: major evolutionary transitions, multicellularity, scaling 11 12 Abstract 13 14 A major challenge in evolutionary biology has been to explain the variation in multicellularity 15 across the many independently evolved multicellular lineages, from slime moulds to 16 humans. Social evolution theory has highlighted the key role of relatedness in determining 17 multicellular complexity and obligateness, however there is a need to extend this to a 18 broader perspective incorporating the role of the environment. In this paper, we formally 19 test Bonner’s 1998 hypothesis that the environment is crucial in determining the course of 20 multicellular evolution, with aggregative multicellularity evolving more frequently on land and 21 clonal multicellularity more frequently in water. Using a combination of scaling theory and 22 phylogenetic comparative analyses, we describe multicellular organisational complexity 23 across 139 species spanning 14 independent transitions to multicellularity and investigate 24 the role of the environment in determining multicellular group formation and in imposing 25 constraints on multicellular evolution. Our results, showing that the physical environment 26 has impacted the way in which multicellular groups form, could shed light on the role of the 27 environment for other major evolutionary transitions.